AI Legal Advisor (Mini Expert System)
1. Introduction
The AI Legal Advisor project is a mini expert system designed to provide basic legal advice. It uses a rule-based approach to analyze user queries and offer guidance on simple legal matters. This system serves as a foundational step towards creating more sophisticated legal expert systems.
2. Prerequisites
• Python: Install Python 3.x from the official Python
website.
• Required Libraries:
- Flask (for deployment): Install using
pip install flask
- pyknow: Install using pip install
pyknow (for rule-based logic).
• Basic Understanding of Legal Rules: Define rules for legal advice (e.g.,
contract laws, employment rights).
3. Project Setup
1. Create a Project Directory:
- Name your project folder, e.g., `AI_Legal_Advisor`.
- Inside this folder, create the main Python script (`legal_advisor.py`).
2. Install Required Libraries:
Ensure Flask and pyknow are installed using `pip`.
4. Writing the Code
Below is an example code snippet for the AI Legal Advisor:
from pyknow import *
class LegalExpertSystem(KnowledgeEngine):
@Rule(Fact(question='employment
termination'))
def employment_rights(self):
print("You are entitled to a
notice period or compensation. Consult your contract for specifics.")
@Rule(Fact(question='contract
breach'))
def contract_breach(self):
print("Document all
instances of breach and notify the other party. Legal action may be an
option.")
@Rule(Fact(question='tenant rights'))
def tenant_rights(self):
print("Ensure your landlord
adheres to the rental agreement. You have rights regarding maintenance and
notice for eviction.")
# Main interaction loop
engine = LegalExpertSystem()
engine.reset()
print("AI Legal Advisor: Welcome! What is your legal query?")
print("Options: employment termination, contract breach, tenant
rights")
query = input("Enter your query: ").lower()
engine.declare(Fact(question=query))
engine.run()
5. Key Components
• Rule-Based Logic: Uses predefined rules to answer legal
questions.
• Knowledge Base: Stores legal rules and conditions for providing advice.
• User Interaction: Provides a simple interface for users to ask questions.
6. Testing
1. Define a variety of legal queries and input them into the system.
2. Validate the responses based on the defined rules.
3. Test edge cases to ensure robustness.
7. Enhancements
• Expand Rule Base: Add more legal rules to handle diverse
queries.
• NLP Integration: Use natural language processing to interpret user input.
• Deployment: Create a web or mobile interface using Flask for accessibility.
8. Troubleshooting
• Incorrect Advice: Verify the defined rules for accuracy.
• Limited Scope: Regularly update the knowledge base with more rules.
• User Input Errors: Implement input validation and suggest corrections.
9. Conclusion
The AI Legal Advisor demonstrates the potential of expert systems in providing basic legal guidance. With further enhancements, it can become a valuable tool for individuals seeking preliminary legal advice.